New methods of solid tumor analysis are needed to enable prediction of distant recurrence and selection of[unreadable] the optimal treatment for individual patients. Current methods for evaluating adjuvant therapy for solid tumors[unreadable] rely on large scale randomized clinical trials to determine efficacy. Such trials are expensive, difficult to[unreadable] perform and require that many patients receive treatment that is either not needed or ineffective. Many[unreadable] believe that future therapy will be "targeted" to specific abnormalities in the tumor. To utilize such targeted[unreadable] therapy novel methods of examining tumor composition for specific targets are needed. In this proposal advanced computational analysis is used to combine molecular profiles (microarrays) with NMR[unreadable] determined metabolite markers, linked with information about biological function from genome and pathway[unreadable] databases. The overall goal is to select and identify combinations of markers in liposarcoma that carry[unreadable] significant diagnostic or prognostic value and to identify potential new therapeutic targets. This study will test[unreadable] the hypothesis that we can:[unreadable] (a) better select patients and tumors that have high or low risk of metastasis and[unreadable] (b) develop new targeted therapeutics for liposarcoma through analysis of signaling pathways critical to[unreadable] liposarcoma differentiation and tumorigenesis.[unreadable] Specific aims: Identify genes and metabolite marker subsets by analysis of integrated gene expression and[unreadable] NMR biochemical profiles that:[unreadable] 1. show associations with liposarcoma (LS) histologic subtype[unreadable] 2. are differentially expressed in LS compared to normal fat tissue and could be used to evaluate signaling[unreadable] pathways central to LS differentiation and tumorigenesis serving as novel therapeutic targets[unreadable] 3. for low grade LS predict the presence of high grade LS elsewhere in the tumor or subsequent presentation[unreadable] with a high grade tumor[unreadable] 4. show association with outcome in liposarcoma.[unreadable] This integrated molecular and biochemical analysis will enable the development of objective and accurate[unreadable] methods for assessing LS diagnosis, progression, risk of metastasis and outcome. The results from this[unreadable] proposal would ultimately enable the identification of new targets, improve the ability to select patients for[unreadable] adjuvant therapy who are at highest risk of relapse and provide a rational approach to selecting combination[unreadable] chemotherapy based on an understanding of protein and lipid metabolism along with solid tumor molecular[unreadable] genetics.[unreadable]